Learning Analytics in Hybrid Manager

Use this section to learn how to apply EDB Hybrid Manager (HM) analytics features to your real-world workloads.

Hybrid Manager enables you to manage and operate advanced analytics capabilities across your Postgres deployments, including:

  • Lakehouse Clusters for high-speed analytical queries on object storage
  • Apache Iceberg and Delta Lake integration for modern data lake architectures
  • Tiered Tables for cost-effective management of large time-series data
  • Unified management of both operational and analytical data through a single control plane

Explore the Learning Content

Concepts

Understand key technologies and patterns that power analytics in Hybrid Manager.

Next topic: How-To Guides for Analytics in Hybrid Manager


Solving Business Problems

See common analytics use cases and how to solve them using Hybrid Manager capabilities.

Next topic: Persona-Based Guide to Using Analytics in Hybrid Manager


Persona-Based Guidance

Find recommended approaches and resources based on your role.

Next topic: How-To Guides for Analytics in Hybrid Manager


How-To Guides

Step-by-step instructions for configuring and using Hybrid Manager analytics features.

Next topic: Analytics Tutorials


Tutorials

In-depth step-by-step projects to apply Hybrid Manager analytics to real scenarios.


Next Steps


Explore Further

Concepts

Understand how Hybrid Manager implements and manages key analytics capabilities, and how core data lakehouse concepts apply within Hybrid Manager.

How-To Guides

Step-by-step guides for configuring and using analytics features in Hybrid Manager, including Lakehouse Clusters, Apache Iceberg, Delta Lake, and Tiered Tables.

Personas

Learn how different technical roles can leverage analytics features in Hybrid Manager to optimize data access, performance, and insights.

Use Cases

Explore common analytics use cases and how Hybrid Manager features support them using Lakehouse Clusters, Tiered Tables, Iceberg, and Delta Lake.


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